Multi-party computation enables secure polynomial control based solely on secret-sharing

Encrypted control systems allow to evaluate feedback laws on external servers without revealing private information about state and input data, the control law, or the plant. While there are a number of encrypted control schemes available for linear feedback laws, only few results exist for the evaluation of more general control laws. Recently, an approach to encrypted polynomial control was presented, relying on two-party secret sharing and an inter-server communication protocol using homomorphic encryption. As homomorphic encryptions are much more computationally demanding than secret sharing, they make up for a tremendous amount of the overall computational demand of this scheme. For this reason, in this paper, we demonstrate that multi-party computation enables secure polynomial control based solely on secret sharing. We introduce a novel secure three-party control scheme based on three-party computation. Further, we propose a novel nparty control scheme to securely evaluate polynomial feedback laws of arbitrary degree without inter-server communication. The latter property makes it easier to realize the necessary requirement regarding non-collusion of the servers, with which perfect security can be guaranteed. Simulations suggest that the presented control schemes are many times less computationally demanding than the two-party scheme mentioned above.

[1]  Pascal Paillier,et al.  Public-Key Cryptosystems Based on Composite Degree Residuosity Classes , 1999, EUROCRYPT.

[2]  Farhad Farokhi,et al.  Secure and Private Implementation of Dynamic Controllers Using Semihomomorphic Encryption , 2018, IEEE Transactions on Automatic Control.

[3]  Tibor Jager,et al.  Encrypted Cloud-based Control using Secret Sharing with One-time Pads , 2019, 2019 IEEE 58th Conference on Decision and Control (CDC).

[4]  Yehuda Lindell,et al.  High-Throughput Semi-Honest Secure Three-Party Computation with an Honest Majority , 2016, IACR Cryptol. ePrint Arch..

[5]  Craig Gentry,et al.  Computing arbitrary functions of encrypted data , 2010, CACM.

[6]  Farhad Farokhi,et al.  Towards Encrypted MPC for Linear Constrained Systems , 2018, IEEE Control Systems Letters.

[7]  Ueli Maurer,et al.  General Secure Multi-party Computation from any Linear Secret-Sharing Scheme , 2000, EUROCRYPT.

[8]  Moritz Schulze Darup,et al.  Encrypted Model Predictive Control in the Cloud , 2019 .

[9]  Dragan Nesic,et al.  Secure Control of Nonlinear Systems Using Semi-Homomorphic Encryption , 2018, 2018 IEEE Conference on Decision and Control (CDC).

[10]  Iman Shames,et al.  Secure and private control using semi-homomorphic encryption , 2017 .

[11]  Masako Kishida,et al.  Encrypted Control System with Quantizer , 2018, IET Control Theory & Applications.

[12]  Vladimir Kolesnikov,et al.  A Pragmatic Introduction to Secure Multi-Party Computation , 2019, Found. Trends Priv. Secur..

[13]  Moritz Schulze Darup,et al.  Encrypted polynomial control based on tailored two‐party computation , 2020, International Journal of Robust and Nonlinear Control.

[14]  Avi Wigderson,et al.  Completeness theorems for non-cryptographic fault-tolerant distributed computation , 1988, STOC '88.

[15]  Takahiro Fujita,et al.  Cyber-security enhancement of networked control systems using homomorphic encryption , 2015, 2015 54th IEEE Conference on Decision and Control (CDC).

[16]  Taher El Gamal A public key cryptosystem and a signature scheme based on discrete logarithms , 1984, IEEE Trans. Inf. Theory.

[17]  Moritz Schulze Darup,et al.  Verschlüsselte Regelung in der Cloud - Stand der Technik und offene Probleme , 2019, Autom..

[18]  Arpita Patra,et al.  BLAZE: Blazing Fast Privacy-Preserving Machine Learning , 2020, IACR Cryptol. ePrint Arch..

[19]  Amos Beimel,et al.  Secret-Sharing Schemes: A Survey , 2011, IWCC.

[20]  Sophie Tarbouriech,et al.  Design of Polynomial Control Laws for Polynomial Systems Subject to Actuator Saturation , 2013, IEEE Transactions on Automatic Control.